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金属粉末选择性激光熔化加工中激光操作窗口预测:基于计算流体动力学模型的开发与验证

Laser Operating Windows Prediction in Selective Laser-Melting Processing of Metallic Powders: Development and Validation of a Computational Fluid Dynamics-Based Model.

作者信息

Ridolfi Maria Rita, Folgarait Paolo, Di Schino Andrea

机构信息

Seamthesis Srl, Via IV Novembre 156, 29122 Piacenza, Italy.

Dipartimento di Ingegneria, Università degli Studi di Perugia, via G. Duranti, 06125 Perugia, Italy.

出版信息

Materials (Basel). 2020 Mar 20;13(6):1424. doi: 10.3390/ma13061424.

DOI:10.3390/ma13061424
PMID:32245059
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7142783/
Abstract

The rapidly ascending trend of additive manufacturing techniques requires a tailoring of existing solidification models and the development of new numerical tools. User-friendly numerical models can be a valid aid in order to optimize operating parameter ranges with the scope to extend the modelling tools to already existing or innovative alloys. In this paper a modelling approach is described simulating the generation of single tracks on a powder bed system in a selective laser melting process. The approach we report attains track geometry as a function of: alloy thermo-physical properties, laser speed and power, powder bed thickness. Aim of the research is to generate a numerical tool able to predict laser power and speed ranges in manufacturing porosity-free printed parts without lack of fusion and keyhole pores. The approach is based on a simplified description of the physical aspects. Main simplifications concern: the laser energy input, the formation of the pool cavity, and the powder bed thermo-physical properties. The model has been adjusted based on literature data providing the track's geometry (width and depth) and relative density. Such data refer to different alloys. In particular, Ti6Al4V, Inconel625, Al7050, 316L and pure copper are considered. We show that the printing process presents features common to all alloys. This allows the model to predict the printing behavior of an alloy from its physical properties, avoiding the need to perform specific experimental activities.

摘要

增材制造技术迅速上升的趋势要求对现有的凝固模型进行定制,并开发新的数值工具。用户友好的数值模型可以成为一种有效的辅助手段,以便优化操作参数范围,从而将建模工具扩展到现有或创新合金。本文描述了一种建模方法,用于模拟选择性激光熔化过程中粉末床系统上单道熔覆的生成。我们报告的方法将熔覆道几何形状作为以下因素的函数来获取:合金热物理性能、激光速度和功率、粉末床厚度。该研究的目的是生成一种数值工具,能够预测制造无孔隙打印部件时的激光功率和速度范围,且不会出现未熔合和匙孔气孔。该方法基于对物理方面的简化描述。主要简化内容涉及:激光能量输入、熔池腔体的形成以及粉末床热物理性能。该模型已根据提供熔覆道几何形状(宽度和深度)及相对密度的文献数据进行了调整。这些数据涉及不同的合金。特别考虑了Ti6Al4V、Inconel625、Al7050、316L和纯铜。我们表明,打印过程呈现出所有合金共有的特征。这使得该模型能够根据合金的物理性能预测其打印行为,而无需进行特定的实验活动。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/43bd/7142783/aa7dade91c77/materials-13-01424-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/43bd/7142783/2eae919dd9b0/materials-13-01424-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/43bd/7142783/65ed677ec32a/materials-13-01424-g002.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/43bd/7142783/2f621e75278b/materials-13-01424-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/43bd/7142783/5b54fabc9315/materials-13-01424-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/43bd/7142783/b3aa85a71203/materials-13-01424-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/43bd/7142783/b16b7abcf7a1/materials-13-01424-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/43bd/7142783/cc71ff696c1a/materials-13-01424-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/43bd/7142783/aa7dade91c77/materials-13-01424-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/43bd/7142783/2eae919dd9b0/materials-13-01424-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/43bd/7142783/65ed677ec32a/materials-13-01424-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/43bd/7142783/41c0b99330dc/materials-13-01424-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/43bd/7142783/2f621e75278b/materials-13-01424-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/43bd/7142783/5b54fabc9315/materials-13-01424-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/43bd/7142783/b3aa85a71203/materials-13-01424-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/43bd/7142783/b16b7abcf7a1/materials-13-01424-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/43bd/7142783/cc71ff696c1a/materials-13-01424-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/43bd/7142783/aa7dade91c77/materials-13-01424-g009.jpg

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